class_docstr: Represents a compiled pipeline with transformers and fitted models.
  
  .. versionadded:: 3.5.0
code: def _transform(
      self, dataset: Union[DataFrame, pd.DataFrame]
  ) -> Union[DataFrame, pd.DataFrame]:
      for t in self.stages:
          dataset = t.transform(dataset)
      return dataset
  
imports: from typing import Any, Dict, List, Optional, Union, cast, TYPE_CHECKING
  import pandas
  from pyspark import keyword_only, since
  from pyspark.ml.connect.base import Estimator, Model, Transformer
  from pyspark.ml.connect.io_utils import ParamsReadWrite, MetaAlgorithmReadWrite
  from pyspark.ml.param import Param, Params
  from pyspark.ml.common import inherit_doc
  from pyspark.sql.dataframe import DataFrame
label_desc: Use image node_id 2 for calling the PipelineModel obj's underlying member method code with example usage: obj._transform(dataset) and returns: dataset